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Title: QUANTITATION AND REPRODUCIBILITY PROBLEMS IN RP- AND SE-HPLC ANALYSES OF CEREAL PROTEINS

Author
item Huebner, Floyd
item Bietz, Jerold

Submitted to: Cereal Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/18/1998
Publication Date: N/A
Citation: N/A

Interpretive Summary: High performance liquid chromatography (HPLC) is used to identify cereal cultivars and to determine quality differences among wheats. Small samples are used and procedures are very sensitive. These factors can cause problems in determining protein amounts and in achieving good reproducibility. We, therefore, studied causes of these problems. Proteins sometimes adhere to stainless steel parts of instruments; use of plastic materials and different solvents corrects these problems. Weighing of flour samples can also be a major source of error. For accurate quantitation duplicate analyses are essential. Use of proper procedures improves the usefulness of HPLC for varietal identification and quality prediction.

Technical Abstract: Reversed-phase (RP-) and size-exclusion high-performance liquid chromatography (SE-HPLC) have become important methods for rapid identification of cereal cultivars and for revealing quality differences. Accuracy and reproducibility are essential for good results. Due to recent changes in these methods, however, such as using smaller columns, lower flow rates, and smaller samples, small procedural errors become more critical for final results. We, therefore, further studied causes and magnitude of problems involving quantitation and reproducibility in RP- and SE-HPLC analyses of cereal proteins. Because of potential problems with protein adsorption to stainless steel system components, we modified systems to contain, insofar as possible, all plastic-type components. Other potentially major problems included weighing flour samples, solvent composition, and data interpretation. Recognizing and dealing with these problems will enhance the accuracy, reproducibility and usefulness of HPLC for varietal identification and quality prediction.